scholarly journals Isohyetal Maps of Daily Maximum Rainfall for Different Return Periods for the Colombian Caribbean Region

Water ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 358 ◽  
Author(s):  
Álvaro González-Álvarez ◽  
Orlando Viloria-Marimón ◽  
Óscar Coronado-Hernández ◽  
Andrés Vélez-Pereira ◽  
Kibrewossen Tesfagiorgis ◽  
...  
Keyword(s):  
Interpolation Method ◽  
Daily Rainfall ◽  
Gumbel Distribution ◽  
Caribbean Region ◽  
Daily Maximum ◽  
Return Periods ◽  
Maximum Rainfall ◽  
Rain Gauges ◽  
Rainfall Frequency ◽  
Data Points

In Colombia, daily maximum multiannual series are one of the main inputs for design streamflow calculation, which requires performing a rainfall frequency analysis that involves several prior steps: (a) requesting the datasets, (b) waiting for the information, (c) reviewing the datasets received for missing or data different from the requested variable, and (d) requesting the information once again if it is not correct. To tackle these setbacks, 318 rain gauges located in the Colombian Caribbean region were used to first evaluate whether or not the Gumbel distribution was indeed the most suitable by performing frequency analyses using three different distributions (Gumbel, Generalized Extreme Value (GEV), and Log-Pearson 3 (LP3)); secondly, to generate daily maximum isohyetal maps for return periods of 2, 5, 10, 20, 25, 50, and 100 years; and, lastly, to evaluate which interpolation method (IDW, spline, and ordinary kriging) works best in areas with a varying density of data points. GEV was most suitable in 47.2% of the rain gauges, while Gumbel, in spite of being widely used in Colombia, was only suitable in 34.3% of the cases. Regarding the interpolation method, better isohyetals were obtained with the IDW method. In general, the areal maximum daily rainfall estimated showed good agreement when compared to the true values.

scholarly journals Analysis of the Behavior of Daily Maximum Rainfall within the Department of Atlántico, Colombia

Water ◽  
2019 ◽  
Vol 11 (12) ◽  
pp. 2453
Author(s):  
Orlando M. Viloria-Marimón ◽  
Álvaro González-Álvarez ◽  
Javier A. Mouthón-Bello
Keyword(s):  
Time Series ◽  
Daily Rainfall ◽  
Information Criterion ◽  
Rain Gauge ◽  
Caribbean Region ◽  
Daily Maximum ◽  
Maximum Rainfall ◽  
Rain Gauges ◽  
Stationary Conditions ◽  
Areal Rainfall

In the Colombian Caribbean region, there are few studies that evaluated the behavior of one of the most commonly used variables in hydrological analyses: the maximum daily rainfall (Pmax-24h). In this study, multiannual Pmax-24h time series from 19 rain gauges, located within the department of Atlántico, were analyzed to (a) determine possible increasing/decreasing trends over time, (b) identify regions with homogeneous behavior of Pmax-24h, (c) assess whether the time series are better suited under either a stationary or non-stationary frequency analysis, (d) generate isohyetal maps under stationary, non-stationary, and mixed conditions, and (e) evaluate the isohyetal maps by means of the calculation of areal rainfall (Pareal) in nine watersheds. In spite of the presence of both increasing and decreasing trends, only the Puerto Giraldo rain gauge showed a significant decreasing trend. Also, three regions (east, central, and west) with similar Pmax-24h behavior were identified. According to the Akaike information criterion test, 79% of the rain gauges showed better fit under stationary conditions. Finally, statistical analysis revealed that, under stationary conditions, the errors in the calculation of Pareal were more frequent, while the magnitude of the errors was larger under non-stationary conditions, especially in the central–south region.

scholarly journals Generating Flood Hazard Maps Based on an Innovative Spatial Interpolation Methodology for Precipitation

Atmosphere ◽  
2021 ◽  
Vol 12 (10) ◽  
pp. 1336
Author(s):  
Mohammad Zare ◽  
Guy J.-P. Schumann ◽  
Felix Norman Teferle ◽  
Ruja Mansorian
Keyword(s):  
Time Scale ◽  
Spatial Interpolation ◽  
Interpolation Method ◽  
Flood Hazard ◽  
Daily Rainfall ◽  
Return Periods ◽  
Hazard Maps ◽  
Rain Gauges ◽  
Fcm Clustering ◽  
Flood Hazard Maps

In this study, a new approach for rainfall spatial interpolation in the Luxembourgian case study is introduced. The method used here is based on a Fuzzy C-Means (FCM) clustering method. In a typical FCM procedure, there are a lot of available data and each data point belongs to a cluster, with a membership degree [0 1]. On the other hand, in our methodology, the center of clusters is determined first and then random data are generated around cluster centers. Therefore, this approach is called inverse FCM (i-FCM). In order to calibrate and validate the new spatial interpolation method, seven rain gauges in Luxembourg, Germany and France (three for calibration and four for validation) with more than 10 years of measured data were used and consequently, the rainfall for ungauged locations was estimated. The results show that the i-FCM method can be applied with acceptable accuracy in validation rain gauges with values for R2 and RMSE of (0.94–0.98) and (9–14 mm), respectively, on a monthly time scale and (0.86–0.89) and (1.67–2 mm) on a daily time scale. In the following, the maximum daily rainfall return periods (10, 25, 50 and 100 years) were calculated using a two-parameter Weibull distribution. Finally, the LISFLOOD FP flood model was used to generate flood hazard maps in Dudelange, Luxembourg with the aim to demonstrate a practical application of the estimated local rainfall return periods in an urban area.

scholarly journals The Effect of Sample Size on Bivariate Rainfall Frequency Analysis of Extreme Precipitation

Proceedings ◽  
2018 ◽  
Vol 7 (1) ◽  
pp. 19 ◽  
Author(s):  
Nikoletta Stamatatou ◽  
Lampros Vasiliades ◽  
Athanasios Loukas
Keyword(s):  
Sample Size ◽  
Frequency Analysis ◽  
Extreme Precipitation ◽  
Goodness Of Fit ◽  
Return Periods ◽  
Goodness Of Fit Test ◽  
Maximum Rainfall ◽  
Rainfall Frequency ◽  
Rainfall Frequency Analysis ◽  
Pseudo Likelihood Estimation

The objective of this study is to compare univariate and joint bivariate return periods of extreme precipitation that all rely on different probability concepts in selected meteorological stations in Cyprus. Pairs of maximum rainfall depths with corresponding durations are estimated and compared using annual maximum series (AMS) for the complete period of the analysis and 30-year subsets for selected data periods. Marginal distributions of extreme precipitation are examined and used for the estimation of typical design periods. The dependence between extreme rainfall and duration is then assessed by an exploratory data analysis using K-plots and Chi-plots and the consistency of their relationship is quantified by Kendall’s correlation coefficient. Copulas from Archimedean, Elliptical, and Extreme Value families are fitted using a pseudo-likelihood estimation method, evaluated according to the corrected Akaike Information Criterion and verified using both graphical approaches and a goodness-of-fit test based on the Cramér-von Mises statistic. The selected copula functions and the corresponding conditional and joint return periods are calculated and the results are compared with the marginal univariate estimations of each variable. Results highlight the effect of sample size on univariate and bivariate rainfall frequency analysis for hydraulic engineering design practices.

scholarly journals Estimation and analysis of the effective rainfall In Tabuk area – Saudi Arabia

2020 ◽  
Vol 28 (14) ◽  
pp. 142-186
Author(s):  
د. فهدة فلاح بن حشر د. فهدة فلاح بن حشر
Keyword(s):  
Saudi Arabia ◽  
Normal Distribution ◽  
Statistical Tests ◽  
Daily Rainfall ◽  
Multiple Comparison ◽  
Daily Maximum ◽  
Effective Rainfall ◽  
Maximum Rainfall ◽  
Significance Level ◽  
Maximum Daily Rainfall

this study examined the effective rainfall in Tabuk area by applying the Lang rainfall factor, De Martonne Index and the (UNEP) arid index. The study methodology was based on a statistical tests using the Normality test (Shapiro-Wilk), the Homogeneity test (Leven test), the ANOVA (LSD test) of the monthly mean of rainfall, the daily maximum rainfall and the total number of rainfall days. The multiple comparison (Tehmane’s Test) had been applied between the studied stations. The results of the Shapiro-Wilk test shows that the distribution of monthly rainfall averages follows normal distribution in all stations except stations Tabuk and Al Bad’ and that the maximum daily rainfall distribution at Duba, Shuw?q, Al Kurr stations is also normal distribution. The Leven test results showed that the significance level was greater than 0.05 and the Leven Test was greater than 0.05 for the average monthly precipitation, for the daily maximum rainfall and for the number of rain days and it indicates the homogeneity of the rainfall variances in the studied stations.The ANOVA analysis of the averages and maximum daily rainfall, shows that the significance level is greater than 0.05 and the LSD test is greater than 0.05 indicating that the differences are not significant. While the LSD was greater than 0.05 for the number of rain days, indicating that the differences between the number of rain days and their distribution at the studied stations are statistically significant differences, and therefore there is no homogeneity in their differences. The results of the Tamhane’s Test of multiple comparison confirmed that the mean level of monthly mean rainfall and daily maximum rainfall is greater than 0.05 indicates that the differences between the monthly rain averages of and the daily maximum rainfall amounts are not significant for 22.2% of total comparisons.The effective rainfall estimate of Lang’s rainfall index shows that the threshold of effective mean rainfall is between 1.3 and 27.4 mm and that the threshold of maximum daily rainfall is 154.1 mm at the station (Al Bad’). Also, the effective rainfall estimate by the DeMartonne index shows that the threshold of average effective rainfall is between 1.2 and 15.2 mm and that the threshold of maximum daily rainfall is 80.4 mm at the station (Al Bad’). Therefore, the effective rainfall estimate by the UNEP index shows that the threshold of average effective rainfall is between 1.8 and 30.3 mm and that the threshold of maximum daily rainfall is 130.5 mm at the station (Al Bad’). Finally, the effective rainfall estimate by the difference between the rainfall and Pan Class“A” Evaporation shows that the threshold of average effective rainfall is between 1.2 and 25.8 mm and that the threshold of maximum daily rainfall is 137.1 mm at the station (Al Bad’).- Key Words:Effective rainfall average, Effective maximum daily rainfall , Number of rainy days, Statistical tests, Lang rainfall factor, DeMartonne index, UNEP arid index, Tabuk area, Saudi Arabia.

Determination of Drainage Coefficient and Bund Height of Rice Fields at Gaya and Bhagalpur Districts in Bihar

2018 ◽  
Vol 5 (01) ◽  
Author(s):  
ASHUTOSH UPADHYAYA ◽  
S. K. Singh
Keyword(s):  
Return Period ◽  
Agricultural Production ◽  
Water Storage ◽  
Daily Rainfall ◽  
Crop Damage ◽  
Distribution Model ◽  
Return Periods ◽  
Maximum Rainfall ◽  
Two Parameter

Rainfall plays an important role in agricultural production, particularly in rainfed areas. Less occurrence of rainfall causes drought like situation and crops suffer due to deficit of water, whereas heavy rainfall occurring for longer duration lead to flood like situation resulting in more runoff, soil erosion and crop damage. Rice can sustain water for little longer period compared to other crops, but this crop also needs drainage. 30 years daily rainfall data was collected at Gaya and Bhagalpur districts and analyzed. Two parameter Gamma distribution model was found fitting well in 1 to 7 consecutive days maximum rainfall corresponding to return periods varying from 2 to 20 years. In order to determine drainage coefficient at Gaya and Bhagalpur districts, depthduration- return period curves were developed. Tangents were drawn on the curves from 100 mm, 150 mm and 200 mm points and slope of these tangents gave the drainage coefficients corresponding to these rain water storage levels. Since 10 years return period is generally considered in design of agricultural structures, so the poin ton Y axis, where tangent drawn on the curves of 10 years return period crosses, gives the bund height. For both Gaya and Bhagalpur bund heights were found as 24 cm and corresponding drainage coefficients as 12.5 and 25 mm/day.

scholarly journals ESTIMATE OF THE INTENSITY-DURATION-FREQUENCY PARAMETERS OF INTENSE RAINFALL FOR THE STATE OF ALAGOAS, BRAZIL

2020 ◽  
Vol 28 ◽  
pp. 314-325
Author(s):  
João Batista Lopes da Silva ◽  
Nicole Lopes Bento ◽  
Gabriel Soares Lopes Gomes ◽  
Alcinei Ribeiro Campos ◽  
Danilo Paulúcio da Silva
Keyword(s):  
Return Period ◽  
Probabilistic Models ◽  
Daily Rainfall ◽  
The State ◽  
Data Series ◽  
Intense Rainfall ◽  
Maximum Rainfall ◽  
Rain Gauges ◽  
Intensity Duration Frequency ◽  
Using Data

The study of the rainfall characteristics is of fundamental importance since the frequency of floods has increased in several parts of Brazil due to anthropic impacts of climatic changes. Thus, this study aimed to determine the parameters of the intense rainfall equation (K, a, b, c) for 52 municipalities in the State of Alagoas using data from 164 rain gauges ta available from the National Water Agency (ANA). The data series were subjected to consistency analysis and further desegregation of maximum daily rainfall to durations of the 5; 10; 15; 20; 25; 30; 60; 360; 480; 600; 720 and 1,440 minutes and return period of 5; 10; 25; 50 and 100 years according to different probabilistic models. The adjustment of the parameters was carried out by means of non-linear regression, with R² greater than 0.949 for all the stations, considering for this purpose one station per municipality, totaling 51 municipalities of study. It was obtained that the maximum rainfall intensity predicted increases with the increase in the return period and decreases with the increase of the duration of the rain. The greater intensities were detected in the mesoregion of Eastern Alagoano and the lowest intensities in the mesoregion of Sertão Alagoano.

scholarly journals Heavy rainfall frequency analysis in the Benin section of the Niger and Volta Rivers basins: is the Gumbel's distribution a one-size-fits-all model?

2021 ◽  
Vol 384 ◽  
pp. 187-194
Author(s):  
Djigbo Félicien Badou ◽  
Audrey Adango ◽  
Jean Hounkpè ◽  
Aymar Bossa ◽  
Yacouba Yira ◽  
...  
Keyword(s):  
Frequency Analysis ◽  
Heavy Rainfall ◽  
Daily Rainfall ◽  
Gumbel Distribution ◽  
Extreme Rainfall ◽  
Type Iii ◽  
Rainfall Frequency ◽  
Pearson Type ◽  
Gumbel’S Distribution ◽  
Rainfall Frequency Analysis

Abstract. West African populations are increasingly exposed to heavy rainfall events which cause devastating floods. For the design of rainwater drainage facilities (to protect populations), practitioners systematically use the Gumbel distribution regardless of rainfall statistical behaviour. The objective of this study is twofold. The first is to update existing knowledge on heavy rainfall frequency analysis in West Africa to check whether the systematic preference for Gumbel's distribution is not misleading, and subsequently to quantify biases induced by the use of the Gumbel distribution on stations fitting other distributions. Annual maximum daily rainfall of 12 stations located in the Benin sections of the Niger and Volta Rivers' basins covering a period of 96 years (1921–2016) were used. Five statistical distributions (Gumbel, GEV, Lognormal, Pearson type III, and Log-Pearson type III) were used for the frequency analysis and the most appropriate distribution was selected based on the Akaike (AIC) and Bayesian (BIC) criteria. The study shows that the Gumbel's distribution best represents the data of 2/3 of the stations studied, while the remaining 1/3 of the stations fit better GEV, Lognormal, and Pearson type III distributions. The systematic application of Gumbel's distribution for the frequency analysis of extreme rainfall is therefore misleading. For stations whose data best fit the other distributions, annual daily rainfall maxima were estimated both using these distributions and the Gumbel's distribution for different return periods. Depending on the return period, results demonstrate that the use of the Gumbel distribution instead of these distributions leads to an overestimation (of up to +6.1 %) and an underestimation (of up to −45.9 %) of the annual daily rainfall maxima and therefore to an uncertain design of flood protection facilities. For better validity, the findings presented here should be tested on larger datasets.

RAINFALL ANALYSIS OF THE KELANTAN BIG YELLOW FLOOD 2014

2016 ◽  
Vol 78 (9-4) ◽  
Author(s):  
Nor Eliza Alias ◽  
Hazim Mohamad ◽  
Wan Yoke Chin ◽  
Zulkifli Yusop
Keyword(s):  
Interpolation Method ◽  
Monsoon Season ◽  
Phase 1 ◽  
Daily Rainfall ◽  
Distribution Model ◽  
Madden Julian Oscillation ◽  
Return Periods ◽  
Phase 2 ◽  
Rainfall Events ◽  
Rainfall Analysis

In December 2014, Kelantan was hit by the worst flood ever recorded. Did the rainfall exceed historical records, how rare are they and what causes them? This paper answers these questions. Estimation of the return periods uses the GEV distribution model and stations with more than 25 years records. Spatial distribution plots of the cumulated rainfall depths were constructed using IDW interpolation method. Four major outcomes are: 1) Spatial rainfall patterns show high amounts of rainfall accumulated by phases (Phase 1- daily rainfall up to 300 mm; Phase 2- daily rainfall up to 500 mm); 2) record breaking rainfall events occurred at 9 stations significantly at Gunung Gagau (1598.9 mm compared to 976.5 mm 7-day cumulated rainfall). Many stations upstream of the river basin experienced ARIs near and over 100 years and several experienced more than 200 years; and 4) Enhanced rainfall were experienced due to the combined effect of the monsoon season, Madden Julian Oscillation and temperature below anomalies at the Siberian High

scholarly journals THE STORMS IN RIO DE JANEIRO CITY IN APRIL 2010

Engevista ◽  
2011 ◽  
Vol 13 (1) ◽  
Author(s):  
Fabio Gomes Coelho ◽  
Mônica De Aquino G. Massera da Hora ◽  
Antonio Ferreira da Hora
Keyword(s):  
Rio De Janeiro ◽  
High Tide ◽  
Daily Maximum ◽  
Historical Records ◽  
Maximum Rainfall ◽  
Rain Gauges ◽  
Rain Gauges Network ◽  
Official Information ◽  
Janeiro City

The Rio de Janeiro City suffered great floods due to the storms that took place between April5th and 6th 2010. According to the official information, the total accumulated in 24 hours was 278mm(considered the worst flood in 44 years, since 1966) and the high tide also contributed to the 60 floodingpoints verified in the whole city. The purpose of the present work is to compare the daily maximum rainfall(P1day) available in Agência Nacional de Águas (ANA) database with the data from the Fundação deGeotécnica da Cidade do Rio de Janeiro (GEO-RIO) rain gauges network and historical records. Theprecipitation gauges registered in ANA and selected for the study were SABÓIA LIMA; IRAJÁ; PRAÇAXV and JARDIM BOTÂNICO and the P1day values found were, respectively, 330.9mm (02/26/1971);339.6mm (02/26/1971); 237.0mm (01/11/1966); and, 242.6mm (01/11/1966). The selected stationsfrom GEO-RIO were TIJUCA; SAÚDE and JARDIM BOTÂNICO and the P1day values found were,respectively, 259.9mm (01/08/1998); 160.8mm (10/24/2007); and 239.0mm (04/06/2010). For the samedays, is also presented an analysis of the recorded tides, observed by Diretoria de Hidrografia e Navegação– DHN, which is a Brazilian navy organization, as a complement to understand the phenomenon. Inconclusion, it was possible to infer that April 2010 event was overcome twice in the last 40 years (February,1971 and January, 1998).

scholarly journals PERENCANAAN REKONSTRUKSI SALURAN INDUK DENGAN MENGGUNAKAN BETON PRECAST DI BANDAR UDARA INTERNASIONAL LOMBOK

2020 ◽  
Vol 4 (4) ◽  
pp. 36-44
Author(s):  
Fitradi Pahala ◽  
Supriadi Supriadi
Keyword(s):  
Precast Concrete ◽  
Drainage System ◽  
Gumbel Distribution ◽  
Daily Maximum ◽  
Distribution Method ◽  
Maximum Rainfall ◽  
Transportation Services ◽  
International Airport ◽  
Rainwater Runoff ◽  
Design Plan

Lombok International Airport is the premier second-class airport located in Tanak Awu, Pujut, Lombok Tengah, Nusa Tenggara Barat which functions to serve transportation services. Lombok International Airport has runway, apron, and two taxiways along with its drainage. The drainage system is needed to prevent puddles of rainwater in the runway, taxiway and apron that can obstruct the aircraft movement. However, looking at the existing condition of the Lombok International Airport’s trunk, it is necessary to conduct research about trunk reconstruction for the next ten years’ time.The research is begun by collecting data such as existing elevation, existing dimension, slope of existing trunk and rainfall data for the last five years. From these data, an analysis of the rainfall plan is carried out using gumbel distribution method. Furthermore, from the results of the analysis, it is obtained the daily maximum rainfall which is used to know the rainwater runoff debit. Re-planning the dimensions of Lombok International Airport’s trunk is carried out to accommodate rainwater runoff debit for the next ten years since the existing dimensions of the existing trunk cannot accommodate rainwater runoff debit for the next ten years. Therefore, it was obtained the design plan for the reconstruction of each segment with a length of 1,2 meters, width of 1,84 meters and height of 1,77 meters. Re-planning the dimensions of the trunk is in precast concrete.

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